Liquefied Petroleum Gas (LPG) is readily available to consumers around the world because LPG is a clean, portable, and efficient source of energy. LPG is currently used by hundreds of millions of people in the world and there are more than 1000 applications. LPG cylinder may leak as a liquid or a gas. If the source of ignition and gas meets LPG can explode or burn. LPG can make the lives of the people in the house endangered and can cause cold burns to the skin. To ensure the safety and security of the consumers using LPG the study aims to develop a device that can detect gas, smoke, and flame from the LPG cylinder and can notify the owner via text messages applying a rule-based approach. The system can display also a warning message and can alarm the owner using a buzzer. The researchers conducted functionality testing with twenty (20) trials in checking the accuracy of the system were obtained a 100% accuracy. This proves that the system is reliable and efficient when using at home by the consumers.

Image classification in remote sensing is defined by categorizing image pixels or raw data sensed by satellites into a distinct set of labels. In this paper, an improved technique for classifying pixels from satellite images is proposed. The technique makes use of the median value of the pixels in the rectangular neighborhood centered at the given pixel to be classified. A scoring system was developed that compares this median value in relation to the expected median values for each of the different classes. The proposed method was tested on Landsat-8 Operational Land Imager (OLI) bands 1 to 7 images and three index images-Normalized Difference Vegetation Index (NDVI), Normalized Difference Built-up Index (NDBI), and Normalized Difference Water Index (NDWI). The experimental results showed an overall accuracy of 94%, a remarkable improvement from the 84% accuracy of the previous work that uses a distance-based classifier. The obtained results indicate that the proposed method can be a better alternative way to classify images in remote sensing.

The study aims to integrate neural network algorithm that predicts students' vulnerability of not having graduation on time to an adaptive learning management system. Neural network is one of the popular machine learning techniques because of its learning algorithm. The learning algorithm is focused on updating weights of the edges in order to produce minimal mean squared error between actual and predicted values. The integration of this platform could lead to much efficient learning management system as LMS is mainly driven to provide individualized and personalized learning tailored to specific requirements and learning preferences. The neural network algorithm is designed to classify students with learning difficulty so that administrators can formulate remediation and academic support policies.

The composite action of reinforcement in the surrounding concrete involve a complex and non-linear mechanism.Inadequate understanding of the underlying interactions may lead to designs with insufficient amount of bond resistance of reinforcing bars in concrete structures.To investigate the effects of various parameters on the bond strength of steel bars in concrete, 54 cube samples with varying embedded reinforcements and strengths were prepared. The samples were cured for 28 days and tested using ultrasonic pulse velocity (UPV) test for sample homogeneity and single pull out test for bond strength.Data gathered in the experiment were used in the development of bond strength model as a function of compressive strength, concrete cover to rebar diameter ratio, embedment length, and UPV using artificial neural network (ANN). Of all the bond strength models considered from various literatures, the neural network model provided the most satisfactory prediction results in good agreement with the bond strength values obtained from the experiment. The UPV parameter was found to be one of the most significant predictors in the neural network model having a relative importance of 20.57%. This suggest that the robust prediction performance of the bond model was attributed to this essential component of the model. The proposed model of this study can be used as baseline information and rapid non-destructive assessment for zone wise strengthening in reinforced concrete.

One of the most significant innovations on the workability of concrete that was achieved in recent years is self-compacting concrete (SCC). This desirable performance can be attained through the addition of admixtures to enhance its properties. In this study, superplasticizers were blended with fly ash and air entraining admixtures and were tested for Slump Flow, V-Funnel, L-Box, U-Box, and Screen Stability tests based on the European Federation of National Associations Representing for Concrete (EFNARC) specifications and guidelines for SSC. Based on the results of the study, Fly ash with spherical smooth texture enhances the lubrication between the concrete particles while the air-entrainer provides microscopic bubbles acting as ball bearings between aggregates. The best result was obtained in the specimens containing 5.0% superplasticizers due to its dispersibility effect and reduced flow resistance. In general, the air entraining agent blended with 3.7% superplasticizer exhibited the best performance in all workability test conducted.

An essential component in decision making for site planners is the availability of risk maps to various geological hazards. Liquefaction in particular can be devastating and impose disastrous damage to existing structures built in earthquake prone areas like the province of Mindoro. Through the aid of in situ data, a simplified method of evaluating earthquake induced liquefaction potential was carried out in this study. This is to address the difficulty and high cost necessary to carry out the development of a liquefaction risk map. Borehole data were collected from different locations in Mindoro and the earthquake liquefaction severity index in each location were calculated using deterministic approach. Results showed that different levels of liquefaction severity were obtained in various areas of Mindoro. There were locations exhibiting manifestations of surface liquefaction due to 7.1 Mw earthquake with a peak ground acceleration of 0.4g. The generated liquefaction severity maps can be utilized as baseline information in selecting appropriate geotechnical intervention for soil improvement and stabilization. Further, the indices can be used as additional dimension of evaluating the holistic reliability of existing engineering structures.

The Philippine algae industry is a multi-billion dollar industry that requires restructuring to further gain global market share. Through the development of new algal bioproducts by strategically repositioning and enabling collaboration with existing industries, the Philippine algal industry aims to enhance its economic status. The decentralized locations of regions in the Philippines make it challenging to select a potential site for the industry. A decision support system is proposed to aid the industry for site selection that evaluates the different regions based on environmental impact, costs, social aspects, and industry presence. In addition, the site assessment considers the viewpoints of the various stakeholders to arrive at a sound and just decision. Thus, a fuzzy analytic hierarchy process (FAHP) method is employed to include the uncertainty in the subjectivity in the viewpoints of different stakeholders such as the academe, the government, and the industry. In addition, the FAHP approach is capable of combining both qualitative and quantitative data. The combined results revealed the level of importance of the main criteria with a combined weight of 43% for the environmental impact, 22% for the costs, 21% for the social aspects, and 14% for the industry presence. The disparity of priorities was observed among the stakeholders where the industry chose costs at 29% above other criteria when compared to the government and the academe which chose environmental impact at 44% and 40%, respectively, among other criteria. The highly preferred sites for the Philippine algae industry were Calabarzon, Northern Mindanao, Western Visayas, and Central Luzon due to the good potential labor force, presence of industries, and available resources in the regions. In order to achieve a harmonious prioritization of criteria among the stakeholders, policies on the encouragement of public investment on regions with marginal income must be considered.

Albeit the potent association between nutrition and health has been repeatedly corroborated in the field of nutrition science through evidence-based approaches, the prevalence of inadequate nutrition among Filipino households is still too high. Therefore, the goal of this study was to pinpoint nutrition challenges faced by Filipino young adults and evaluate whether a personalized nutrition knowledge-based system is a potential nutrition intervention tool. A mixed-methods needs analysis approach was operated to arrive at a panoramic profile of a nutrition knowledge-based system through the participation of respondents in an online survey (n = 85) and focus groups (n = 4). The assessment was grounded from the influencing factors of health and nutritional status such as food selection, nutrition barriers, poor eating habits, nutrition knowledge, and with the inclusion of nutrition application for technical feedback. The findings exploited the fact that people do not track what they eat, let alone the nutrients it contained, which eventually leads to undereating or overeating. There was also a commonness in lack of nutrition knowledge to make healthier food choices. Fortunately, the willingness of participants to point their directions towards a healthier lifestyle through the use of a nutrition knowledge-based system was evident. The paper then concluded with recommendations for future studies and how its findings might be utilized for the development of a personalized nutrition system.

Blood banking is the process of collecting, separating and warehousing blood. There are numerous file-based repositories of blood bank management that exist for storing data for blood bank ecosystem such as hospitals and centers. This functions for maintaining the information of donors, availability of blood, and transaction information. Currently, these systems are effort intensive, costly, and failed to achieve efficiency in terms of its filtering mechanism which makes repository penetrating faster and reliable. This paper introduces a new design for blood banking ecosystem with proper filtering solution using frame-based approach. The system has three major features: (1) blood camp setup module, (2) stocks management module which includes the blood donation and blood releasing, and (3) the filtering system module which shows the nearest blood camp with the available blood type based on the patients’ needs. Also, with the use of frame-based approach as filtering method, the system is more efficient and reliable compared to other blood banking repository systems. The system’s functionality was tested for its efficiency, usability, and reliability and the results are revealed in the survey. Conclusions and future work were also provided in this paper.

The blockchain phenomena is no longer about Bitcoin or cryptocurrency, it is beyond a common protocol to make it nearly impossible to create fraudulent transaction. Blockchain based architecture overall performance is subjected to storage expenses with high computational cost. This paper designed a new consensus protocol for Blockchain using Content Addressable Pattern with the adaptation of modified SHA256 algorithm. Although government, business and other entities interest of adapting blockchain to their processes, the complexity issues and operational cost is still a challenge to date. With the newly design consensus protocol the process of validating the transaction that involves tedious mining or solving cryptographic puzzles has been eliminated and move towards using signature to authenticate the transaction. Concatenation of all these elements is a generated hash value using modified SHA256. Since the hash is secured, the transaction is secured. Thus, the implementation of off-chain chanel instead of global consensus addresses the complexity and high computational cost of blockchain technology.